Comparison
gpt4all vs ray-llm
Verdict
Pick gpt4all when tags unique to gpt4all: ai-chat, c++, llm-inference; pick ray-llm when tags unique to ray-llm: ray, llm, llm-serving.
Markdown twin · gpt4all alternatives · ray-llm alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | gpt4all | ray-llm |
|---|---|---|
| Maintenance | Dormant (409d since push) As of today · github_public_v1 | Archived (485d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- gpt4all
- GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
- ray-llm
- RayLLM - LLMs on Ray (Archived). Read README for more info.
Stars
- gpt4all
- 77k
- ray-llm
- 1.3k
Forks
- gpt4all
- 8.3k
- ray-llm
- 90
Open issues
- gpt4all
- 768
- ray-llm
- 0
Language
- gpt4all
- C++
- ray-llm
- -
Adopt for
- gpt4all
- -
- ray-llm
- -
Persona
- gpt4all
- -
- ray-llm
- -
Runtime
- gpt4all
- -
- ray-llm
- -
License
- gpt4all
- MIT
- ray-llm
- -
Last pushed
- gpt4all
- May 27, 2025
- ray-llm
- Mar 13, 2025
Categories
- gpt4all
- LLM Frameworks, Inference & Serving
- ray-llm
- LLM Frameworks, Inference & Serving
Trust and health
Maintenance
- gpt4all
- Dormant (18%)
- ray-llm
- Archived (8%)
Days since push
- gpt4all
- 409d
- ray-llm
- 485d
Archived on GitHub
- gpt4all
- No
- ray-llm
- Yes
Open issues (now)
- gpt4all
- 768
- ray-llm
- 0
Full report
- gpt4all
- Trust report
- ray-llm
- Trust report
Choose gpt4all if…
- Tags unique to gpt4all: ai-chat, c++, llm-inference.
- More GitHub stars (77k vs 1.3k) - visibility, not fit.
When NOT to use gpt4all
- Last GitHub push was 410 days ago (dormant maintenance, May 27, 2025). Validate activity before betting a new project on gpt4all.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Choose ray-llm if…
- Tags unique to ray-llm: ray, llm, llm-serving.
- Leaner open-issue backlog (0).
When NOT to use ray-llm
- ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nomic-ai/gpt4all) · observed Jul 11, 2026
- GitHub forks (nomic-ai/gpt4all) · observed Jul 11, 2026
- Last push (nomic-ai/gpt4all) · observed May 27, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ray-project/ray-llm) · observed Jul 11, 2026
- GitHub forks (ray-project/ray-llm) · observed Jul 11, 2026
- Last push (ray-project/ray-llm) · observed Mar 13, 2025
- License file (unknown) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt4all 77k · ray-llm 1.3k (synced Jul 11, 2026).
Common questions
- What is the difference between gpt4all and ray-llm?
- gpt4all: GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.. ray-llm: RayLLM - LLMs on Ray (Archived). Read README for more info.. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt4all over ray-llm?
- Choose gpt4all over ray-llm when Tags unique to gpt4all: ai-chat, c++, llm-inference; More GitHub stars (77k vs 1.3k) - visibility, not fit.
- When should I choose ray-llm over gpt4all?
- Choose ray-llm over gpt4all when Tags unique to ray-llm: ray, llm, llm-serving; Leaner open-issue backlog (0).
- When should I avoid gpt4all?
- Last GitHub push was 410 days ago (dormant maintenance, May 27, 2025). Validate activity before betting a new project on gpt4all. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- When should I avoid ray-llm?
- ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Is gpt4all or ray-llm more popular on GitHub?
- gpt4all has more GitHub stars (77,386 vs 1,263). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt4all and ray-llm open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to gpt4all or ray-llm?
- GraphCanon lists graph-backed alternatives at gpt4all alternatives and ray-llm alternatives (gpt4all markdown twin, ray-llm markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, gpt4all or ray-llm?
- gpt4all: Dormant. ray-llm: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for gpt4all and ray-llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt4all trust report; ray-llm trust report.